code: def get_rgb_loss(
      self, rgb_values, rgb_gt, network_object_mask, object_mask
  ):
      if (network_object_mask & object_mask).sum() == 0:
          return torch.tensor(0.0).cuda().float()
  
      rgb_values = rgb_values[network_object_mask & object_mask]
      rgb_gt = rgb_gt.reshape(-1, 3)[network_object_mask & object_mask]
      rgb_loss = self.l1_loss(rgb_values, rgb_gt) / float(
          object_mask.shape[0]
      )
      return rgb_loss
  
file_path: insightface/reconstruction/PBIDR/code/model/loss.py
imports: import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 2 for calling the IFLoss obj's underlying member method code with example usage: obj.get_rgb_loss(rgb_values, rgb_gt, network_object_mask, object_mask) and returns: rgb_loss, torch